int8 represent in numpy?int8 is an integer type that uses 8 bits to store values. It can hold numbers from -128 to 127.
int16 use and what is its value range?int16 uses 2 bytes (16 bits) and can store integers from -32,768 to 32,767.
int32 over int8 in numpy arrays?int32 can store much larger numbers (from about -2 billion to 2 billion) than int8. Use it when you need bigger integer values.
int64 and int32?int64 uses 8 bytes and can store much larger integers (from about -9 quintillion to 9 quintillion) compared to int32 which uses 4 bytes.
Choosing smaller integer types like int8 saves memory but limits the range of values. Larger types like int64 use more memory but can store bigger numbers.
int8 uses 1 byte (8 bits) of memory.
int16 can store?int16 stores values from -32,768 to 32,767.
int64 can store the largest integer values among these options.
int32 uses 4 bytes (32 bits) of memory.
Storing a number larger than the max value causes overflow, wrapping around to negative or unexpected values.